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Evidence-Based Education with Learning Analytics

Date: Monday, 19th August 2019
Time: 02:00 PM
Location: CIC Ideation Studio

This talk will provide an overview of the Educational Big Data and Learning Analytics research project in Japan. This project proposes an information infrastructure for learning analytics for evidence-based education. The educational data is mainly collected from e-book system called BookRoll that allows students to capture their reading process.
This talk will show learning analytics tools and initial findings in our project.

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Short Bio

Hiroaki Ogata is a Professor at the Academic Center for Computing and
Media Studies, and the Graduate School of Informatics, Kyoto
University, Japan. His research interests include Computer Supported
Ubiquitous and Mobile Learning, CSCL, CALL, and Learning Analytics. He
has published more than 400 peer-reviewed papers including SSCI
Journals and international conferences. He has received APSCE
Distinguished Researcher Award in 2014, and several Best Paper Awards.
Also he gave keynote lectures in several countries. He is an associate
editor of IEEE Transactions on Learning Technologies. RPTEL and IJMLO,
and also an editorial board member of IJCSCL, IJAIED and SLE. He is an
EC member of SOLAR and APSCE.

Advanced Learning Analytics for Face-to-face Lecture Support

This conversation will introduce advanced tools for supporting learning and teaching in face-to-face lectures. In Kyushu University, Japan, M2B learning support system is available, which consists of three major components; Moodle, Mahara, and BookRoll. Moodle and Mahara are used as a learning management system and portfolio system, respectively. BookRoll is a self-developed system, which provides not only digital textbooks to students, but also page-wise recommendation information related to the contents in the page, page-wise response button to grasp the difficulty of contents, etc. All students in the university bring their own devices to lecture rooms, so that they can access the digital learning environment even in the face-to-face lecture style.Learning and teaching support tools have been developed working on the M2B learning support system. During the lecture, for instance, a teacher explains the contents of the materials, and students browse the materials on their laptops. Learning logs are sequentially analyzed, and the results including real-time information regarding how many students were following the lecture, how many students were browsing previous pages are immediately visualized on the web interface. Therefore, the teacher can check the latest student activities and can adaptively control the speed of the lecture according to the students.

Short Bio

Atsushi Shimada received the D.E. degrees from Kyushu University in 2007. He is an Associate Professor of Faculty of Information Science and Electrical Engineering, Kyushu University. He also worked as a JST-PRESTO researcher since 2015 to 2019. His current research interests include learning analytics, pattern recognition and media processing. He received MIRU Interactive Presentation Award (2011, 2017), MIRU Demonstration Award (2015), Background Models Challenge 2012 The First Place (2012), PRMU research award (2013), SBM-RGBD Challenge The First Place (2017), ITS Symposium Best Poster Award (2018), JST PRESTO Interest Poster Award (2019), IPSJ/IEEE-Computer Society Young Computer Researcher Award(2019).